batch Snapchat Marketing to PostgreSQL in minutes
Snapchat is a multi-media messaging and social media platform that is often included in social media marketing campaigns. This connector allows you to extract data related to your organization, its ad campaigns, creative media, and more through the Snapchat Marketing API.
PostgreSQL is one of the most powerful open source relational databases in the world. It’s developed a broad community in its 30-plus year history.
It features ACID transactions and is designed to handle a range of workloads from single machines to distributed architectures with replication.
Estuary integrates with an ecosystem of free, open-source connectors to extract marketing data from Snapchat with low latency, allowing you to replicate that data to various systems for both analytic and operational purposes. Snapchat marketing data can be organized into a data lake or loaded into other data warehouses or streaming systems.
Data can then be directed to Postgres using materializations that are also open-source. Connectors have the ability to keep databases as up to date as posible without incurring costs, allowing Postgres to be kept up to date with millisecond latency.
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Estuary helps move data from
Snapchat Marketing to PostgreSQL in minutes with millisecond latency.
Estuary helps move data fromSnapchat Marketing to PostgreSQL in minutes with millisecond latency.
Estuary enables the first fully managed ELT service that combines both millisecond-latency and point-and-click simplicity. Flow empowers customers to analyze and act on both historical and real-time data across their analytics and operational systems for a truly unified and up-to-date view.
Flow is developed in the open and utilizes open source connectors that are compatible with a community standard. By making connectors interchangeable with other systems, the Estuary team hopes to expand the ecosystem for everyone’s benefit, empowering organizations of all sizes to build frictionless data pipelines, regardless of their existing data stack.